RBS: Putting analytics at the heart of the organization

Jessica Twentyman — March 2014

How Alan Grogan, chief analytics officer for the international bank’s Customer Solutions Group, has fostered a data-driven culture.

Business leaders who harbor ambitions to take on the big data challenge regard access to vast amounts of customer behavior data — as well as data on what influences that behavior — as the root business-changing insight. Most are just getting off the starting blocks with their efforts to secure such data, but a few have been working towards such a goal for years — and created dedicated teams to do so.

Alan Grogan, chief analytics officer, RBS

Royal Bank of Scotland (RBS), the state-owned financial group that controls the UK’s NatWest, Ulster Bank in Northern Ireland and Citizens Bank in the US, certainly has the scale of data to play with. In the UK alone, it counts around 45% of large businesses as account holders, while it also stands as the country’s biggest lender to small and medium-sized enterprises.

That gives the bank unprecedented visibility into how those hundreds of thousands of businesses interact with each other and with the bank itself, says Alan Grogan, the chief analytics officer (CAO) at the bank’s Customer Solutions Group since last year. By supplementing its swathes of internal data with a wealth of third-party information from providers such as Experian, Bureau van Dijk and Standard & Poor’s, as well open government data, RBS has been able to build a vast map of interactions — both at home and abroad — and to model the likely impact of business disruptions to their operations — almost as they happen.Data-driven decisions

Take, for example, the unfolding situation in Ukraine: in recent years, around one-third of that country’s exports have gone to the European Union, in the form of iron, steel, mining products, and agricultural products, and machinery, according to European Commission figures. So it stands to reason that business leaders in the EU are concerned about the likely impact of developments in the region on member-country businesses.

By using sophisticated data analysis techniques, Grogan and his team can explore the likely impact on different business customers as the price for raw materials rises, as well as and monitor core currencies that they used to explore how cross-currency interdependencies might increase or decrease supply-chain risk.

That’s just one instance. “We’re putting analytics at the heart of all decision-making at RBS,” he says. Indeed, he believes that kind of deep analytics will become a core competency for all successful banks. As part of the management restructuring of RBS (the bank was taken under state control in 2008 at the height of the credit crisis of 2008) Grogan was given broad responsibility to design, build and lead a new Analytics analytics unit for RBS. Now, after four years in which his unit’s remit grew has grown to include providing group-wide thought-leadership on product, customer and market analytics, he’s convinced the bank is “in a good place with analytics.” But that execution has underscored just how multi-faceted the role of CAO has to be in order to achieve such success.Facets of a CAO

A chief analytics officer CAO certainly has to demonstrate the core aspects of a CTO, says Grogan — someone who can run advanced infrastructure and overseeing a technology strategy and transformation program. When he first joined RBS in 2009, the bank’s analytical capabilities, he admits painfully, were “virtually non-existent.” Today, he claims, they’re “market-leading, in global terms.”

Key to that was the implementation in 2013 of a vast data warehouse based on Microsoft’s SQL Server 2012 Parallel Data Warehouse technology. Populating that data warehouse, meanwhile, required elements of the roles more akin to that of both a chief data officer and a chief information officer. “Not only do I need to fill the infrastructure with [high-quality] data, but I need to ensure that the data is relevant and timely, and that it’s managed within strict guidelines of security and governance.” says Grogan.

The RBS data warehouse, he explains, draws data from a wide range of operational and analytic databases scattered around the bank. Every business day, vast volumes of new data are added to these stores. For business customers alone, RBS processes around 400 in-branch transactions per minute and over more than £7 billion’s ($12bn) worth of electronic payments each business day, all of which has to be gathered and readied for analysis.

“My job is to interface with every department within the bank to understand their data needs and provide a joined-up, coherent view of RBS.”

But understanding how that data will be used is another critical facet of the chief analytics officer’s CAO’s role: CAOs need to be business partners, he says. “I interface with every department within the bank, including finance, sales, operations and risk, to understand what they need from data and to provide them with a joined-up, coherent view of the RBS world,” he says.

Of course, he is hardly alone in creating such business value. Grogan is acutely aware that finding — and retaining — the best analytics staff is the key to unlocking the potential of big data.

“We have hugely talented data scientists and analysts working at RBS, and a very low attrition rate — something and I want to keep it that way,” he says. That means taking on the role of coach for the whole team, making sure they have the tools they need and the freedom to explore data in ways that are interesting to them and, hopefully, meaningful to the bank. Grogan also believes it is important to maintain a pipeline of capability; so he works with several universities to identify emerging talent, as well as with other companies and government agencies on developing thought- leadership in analytics.

Like other CAOs, Grogan has only had that newly coined title since 2013 (others notable CAOs are at Havas Media, Caesars Entertainment and KeyBank). But, what is clear from his experience, the IT industry expect to see the role added to the CXO lexicon as many more companies seek to realize the value of their big data.

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